Michael Bockmayr
1 week ago
PhD Student Position in Multimodal Machine Learning for Oncology Forschungsinstitut Kinderkrebs-Zentrum Hamburg in Germany
Degree Level
PhD
Field of study
Oncology
Funding
BMFTR-funded consortium position; PhD student role at E13, 100% employment. The post indicates funded employment rather than self-funded study, with no stipend amount stated.
Country
Germany
University
German Cancer Research Center (DKFZ)

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About this position
PhD opportunity in multimodal machine learning, computational oncology, and medical bioinformatics at the Computational Pediatric Oncology group of the Forschungsinstitut Kinderkrebs-Zentrum Hamburg and Universitätsklinikum Hamburg Eppendorf in Germany.
The position is part of a BMFTR-funded consortium and is advertised as a PhD Student (E13, 100%) role. The project focuses on developing methodologically challenging AI approaches that can directly improve the diagnostics and treatment of cancer patients, with collaboration involving Dr. Mina Jamshidi (BIFOLD) and Philipp Jurmeister (LMU).
Ideal applicants should have a strong background in computational sciences and machine learning. The post is especially relevant for candidates interested in applying AI to pediatric hematology and oncology, cancer research, and biomedical data analysis.
Applications must be submitted via the official portal; the post explicitly says that applications by email or LinkedIn cannot be processed. For questions, contact [email protected].
Funding details
BMFTR-funded consortium position; PhD student role at E13, 100% employment. The post indicates funded employment rather than self-funded study, with no stipend amount stated.
What's required
Strong background in computational sciences and machine learning is requested. The role is for a PhD student (E13, 100%) working on methodologically challenging approaches in multimodal machine learning for oncology. Applications must be submitted through the official portal; email or LinkedIn applications are not accepted.
How to apply
Apply through the official portal linked in the post. Do not submit applications by email or LinkedIn. Contact Michael Bockmayr directly only for additional information.
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